Documentation
/ Guide méthodologique
: 
| VII.2. Minimisation techniques | ||
|---|---|---|
 | Chapter VII. The Calibration module |  |
The theory behind this method may seem very basic as it consists mainly in a point estimation of a valid configuration that could be performed without accounting for underlying uncertainty. This view is overly simplistic, since numerical optimisation problems are not simple, even for single-objective optimisation due, for instance, to:
the regularity of the cost function, the presence of possible local minima, and the computational cost involved;
the dimensionality of the input space and the potentially complex constraints on the inputs.
These challenges can be addressed through an appropriate problem formulation and the use of a suitable optimisation algorithm. However, these choices are not always straightforward, especially when calibration is confronted with identi- fiability issues. For further methodological aspects on these issues, see Chapter VI.
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| Chapter VII. The Calibration module |  | VII.3. Analytical linear Bayesian estimation |